AI agents: what changes when a model gets tools
An agent is a language model that can call things — a search, a calculator, a database — look at what came back, and decide what to do next. Give this one different tools and watch the plan it forms change, including the times it picks the wrong tool or loops. That failure mode is the point. Agents are unusually easy to demonstrate and unusually hard to make reliable, because every step can fail in a way the next step does not notice. Watching a plan go wrong in a sandbox is the cheapest possible version of that lesson, and it is the one CAWAE builds on.
AI Agents
Give an agent tools
An agent is a language model in a loop: reason → pick a tool → act → observe → repeat. On its own it can only think. Attach tools and memory below and watch which steps of a real task it can finally complete.
Task: Plan a client meeting and brief the team on Q3 numbers.
- Recall the client's preferences and past meetings.
- Look up the client's recent news.
- Pull the Q3 sales figures.
- Compute quarter-over-quarter growth.
- Find a free slot and create the event.
- Send the brief and invite to the team.
The model's reasoning is the same — tools are what turn thinking into doing.